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[null,"1.","Record Nr.",null,"UNISA996390208603316"]
[null,null,"Autore",null,"Jerome Stephen <fl. 1604-1650.>"]
[null,null,"Titolo",null,"Seauen helpes to Heauen [[electronic resource] ] : shewing 1. How to auoide the curse. 2. How to beare the crosse. 3. How to build the conscience. 4. How with Moses to see Canaan. 5 Simeons dying song, directing to liue holily and dye happily. 6. Comforts for Christians against distresses in life, & feare of death. 7 Feruent prayers to beare sicknesse patiently, and dye preparedly. The third edition: corrected and enlarged by Steuen Ierome, late preacher at St. Brides. Seene and allowed"]
[null,null,"Pubbl/distr/stampa",null,"London, : Printed I. W[hite] and A[ugustine] M[athewes] for Roger Iackson, and are to bee sold at his shop, neare to the Conduit in Fleetstreet, 1620"]
[null,null,"Descrizione fisica",null,"[22], 80, 73-88, [14], 537 [i.e. 538] p"]
[null,null,"Soggetti",null,"Christian life"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","An enlarged edition of: Moses his sight of Canaan."]
[{"$nulls":4},"The words \"1. How to auoide .. and dye preparedly.\" are bracketed together on the title page."]
[{"$nulls":4},"Printers' names from STC."]
[{"$nulls":4},"\"Moses his sight of Canaan. With Simeon his dying-song\" has separate title page dated 1619, and separate pagination; register is continuous."]
[{"$nulls":4},"P. 538 misnumbered 537."]
[{"$nulls":4},"Identified as STC 14515 on UMI microfilm."]
[{"$nulls":4},"Reproduction of the original in the British Library."]
[null,null,null,"Sommario/riassunto","eebo-0018"]
[null,"2.","Record Nr.",null,"UNINA9910637709903321"]
[null,null,"Autore",null,"Hemanth D. Jude"]
[null,null,"Titolo",null,"Smart Applications with Advanced Machine Learning and Human-Centred Problem Design / / by D. Jude Hemanth, Utku Kose, Junzo Watada, Bogdan Patrut"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023"]
[null,null,"ISBN",null,"3-031-09753-X"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (801 pages)"]
[null,null,"Collana",null,"Engineering Cyber-Physical Systems and Critical Infrastructures, , 2731-5010 ; ; 1"]
[null,null,"Disciplina",null,"016.403"]
[{"$nulls":4},"006.3"]
[null,null,"Soggetti",null,"Computational intelligence"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Engineering - Data processing"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Data Engineering"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- General Committees -- Honorary Chairs -- General Chair -- Conference Chairs -- Organizing Committee -- Secretary and Social Media -- Accommodation and Registration/Venue Desk -- Travel/Transportation -- Web/Design/Conference Session -- Scientific Committee -- Keynote Speaks -- ICAIAME 2021 Keynote Speakers -- Foreword -- Preface -- Contents -- About the Conference -- Scope/Topics -- Conference Scope/Topics (as not limited to) -- Conference Posters -- 1 Implementation of Basic Math Processing Skills with Neural Arithmetic Expressions in One and Two Stage Numbers -- 1.1 Introduction -- 1.1.1 Neural Arithmetic Expressions and Logic Units -- 1.1.2 Long Short-Term Memory Algorithm -- 1.2 Related Work -- 1.3 Proposed Method -- 1.4 Experimental Findings -- 1.5 Conclusions -- References -- 2 An Example Application for Early Diagnosis of Retinal Diseases Using Deep Learning Methods -- 2.1 Introduction -- 2.2 Material and Method -- 2.2.1 Material -- 2.2.2 Method -- 2.3 Research Findings -- 2.4 Discussion -- 2.5 Results -- References -- 3 Autonomous Parking with Continuous Reinforcement Learning -- 3.1 "]
[{"$nulls":4},"Introduction -- 3.2 Related Works -- 3.2.1 Deep Q Networks -- 3.2.2 Deep Deterministic Policy Gradient Algorithm -- 3.2.3 Twin Delayed Temporal Difference Algorithm -- 3.2.4 Soft Actor Critic Algorithm -- 3.2.5 Hindsight Experience Replay Algorithm -- 3.2.6 Parking Environment Simulation Model -- 3.3 Experiments and Results -- 3.4 Conclusions and Future Work -- References -- 4 Design and Manufacturing of a 3 DOF Robot with Additive Manufacturing Methods -- 4.1 Introduction -- 4.2 Material and Method -- 4.2.1 Material -- 4.3 Method -- 4.4 Findings and Discussion -- 4.5 Conclusion -- References -- 5 Real-Time Mask Detection Based on Artificial Intelligence Using Renewable Energy System Unmanned Aerial Vehicle -- 5.1 Introduction -- 5.2 Related Studies."]
[{"$nulls":4},"5.3 Material and Method -- 5.3.1 Material -- 5.3.2 Material and Method -- 5.4 Research Findings -- 5.5 Conclusion -- References -- 6 Investigation of Effect of Wrapping Length on the Flexural Properties of Wooden Material in Reinforcement with Aramid FRP -- 6.1 Introduction -- 6.2 Material and Method -- 6.3 Results -- 6.4 Conclusions -- References -- 7 Deep Learning-Based Air Defense System for Unmanned Aerial Vehicles -- 7.1 Introduction -- 7.2 Material and Method -- 7.2.1 Material -- 7.2.2 Method -- 7.3 Research Findings -- 7.3.1 MobileNetV2 Training Results -- 7.3.2 Xception Training Results -- 7.3.3 InceptionV3 Training Results -- 7.4 Results -- References -- 8 Strategic Framework for ANFIS and BIM Use on Risk Management at Natural Gas Pipeline Project -- 8.1 Introductıon -- 8.2 Literature -- 8.3 Materials and Methods -- 8.3.1 Artificial Neural Networks (ANN) -- 8.3.2 Structure of Artificial Neural Network -- 8.3.3 Fuzzy Inference System -- 8.3.4 Adaptive Neuro-Fuzzy Inference System-ANFIS -- 8.3.5 What is the Building Information Modelling (BIM) -- 8.3.6 Methods -- 8.4 Results -- 8.5 Conclusion -- References -- 9 Predicting Ethereum Price with Machine Learning Algorithms -- 9.1 Introduction -- 9.2 Related Works -- 9.3 Method and Material -- 9.3.1 Used Methods -- 9.3.2 Data Collecting -- 9.3.3 Method -- 9.4 Discussion and Results -- 9.5 Conclusions and Future Work -- References -- 10 Data Mining Approachs for Machine Failures: Real Case Study -- 10.1 Introductıon -- 10.2 Literature -- 10.3 Methods -- 10.3.1 Re-processing the Data -- 10.3.2 Methods -- 10.4 Results -- 10.5 Conclusion -- References -- 11 Classification of People Both Wearing Medical Mask and Safety Helmet -- 11.1 Introduction -- 11.2 Materials and Methods -- 11.2.1 Dataset -- 11.2.2 Method -- 11.2.3 Single Deep Neural Network -- 11.2.4 Double Deep Neural Network."]
[{"$nulls":4},"11.3 Conclusions and Future Work -- References -- 12 Anonymization Methods for Privacy-Preserving Data Publishing -- 12.1 Introduction -- 12.2 Big Data Definition -- 12.3 Data Anonymization -- 12.3.1 Protection Methods with Anonymization -- 12.3.2 Anonymization and Protection Models -- 12.4 Literature Review -- 12.5 Comparison of Existing Studies -- 12.6 Conclusion -- References -- 13 Improving Accuracy of Document Image Classification Through Soft Voting Ensemble -- 13.1 Introduction -- 13.2 Related Works -- 13.3 Methodology -- 13.3.1 Document Image Classification -- 13.3.2 Image Pre-processing -- 13.3.3 Convolutional Neural Network -- 13.3.4 Soft Voting -- 13.4 Experiments and Result -- 13.4.1 Dataset -- 13.4.2 Evaluation Metrics -- 13.4.3 Experiments -- 13.5 Conclusion -- References -- 14 Improved Performance of Adaptive UKF SLAM with Scaling Parameter -- 14.1 Introduction -- 14.2 Adaptive UKF SLAM -- 14.3 Simulation Results and Discussions -- 14.4 Conclusion and Suggestions -- References -- 15 An Adaptive EKF Algorithm with Adaptation of Noise Statistic Based on MLE, EM and ICE -- 15.1 Introduction -- 15.2 Methods -- 15.2.1 Extended Kalman Filter (EKF) "]
[{"$nulls":4},"-- 15.2.2 Unscented Kalman Filter (UKF) -- 15.2.3 Adaptive Extended Kalman Filter (AEKF) -- 15.2.4 Data Association -- 15.2.5 AEKF-SLAM Algorithm -- 15.3 Simulation Results and Discussion -- 15.4 Conclusions and Future Work -- References -- 16 Artificial Intelligence Based Detection of Estrus in Animals Using Pedometer Data -- 16.1 Introduction -- 16.2 Related Works -- 16.3 Method and Material -- 16.3.1 Architectural Design -- 16.3.2 Devices -- 16.3.3 Electronic Circuit Design -- 16.3.4 Proposed Algorithms -- 16.4 Discussion and Result -- 16.5 Conclusions and Future Work -- References -- 17 Enhancing Lexicon Based Sentiment Analysis Using n-gram Approach -- 17.1 Introduction."]
[{"$nulls":4},"17.2 Sentiment Lexicons -- 17.2.1 Vader -- 17.2.2 TextBlob -- 17.2.3 Afinn -- 17.2.4 SentiWordNet -- 17.3 Proposed Framework -- 17.3.1 Pre-processing Step -- 17.3.2 N-gram Extraction -- 17.3.3 Feature Space Construction -- 17.4 Experimental Results -- 17.5 Conclusion -- References -- 18 A Comparison of Word Embedding Models for Turkish -- 18.1 Introduction -- 18.2 Data and Data Preprocessing Steps -- 18.3 Method -- 18.3.1 Embedding Models -- 18.3.2 Classification Model -- 18.4 Experiments -- 18.5 Conclusion -- References -- 19 The Unfairness of Collaborative Filtering Algorithms' Bias Towards Blockbuster Items -- 19.1 Introduction -- 19.2 Related Works -- 19.3 Description of Blockbuster Items -- 19.4 Blockbuster Bias in User Profiles -- 19.4.1 The Propensities of Users for Blockbuster Items -- 19.4.2 Profile Size and Blockbuster Bias -- 19.5 Different User Groups in Terms of Inclination for Blockbuster -- 19.6 Algorithmic Propagation of Blockbuster Bias -- 19.6.1 Blockbuster Bias in Recommendations for Different User Groups -- 19.7 Conclusion and Future Work -- References -- 20 Improved Gradient-Based Optimizer with Dynamic Fitness Distance Balance for Global Optimization Problems -- 20.1 Introduction -- 20.2 Related Works -- 20.2.1 GBO -- 20.2.2 Dynamic Fitness-Distance Balance (dFDB) -- 20.2.3 Improved GBO with Dynamic Fitness Distance Balance -- 20.3 Experimental Study -- 20.3.1 Settings -- 20.3.2 Benchmark Problems -- 20.3.3 Constrained Engineering Design Problems -- 20.4 Analyze Results -- 20.4.1 Statistical Analysis Results -- 20.4.2 Convergence Analysis Results -- 20.4.3 Results for Engineering Design Problems -- 20.5 Conclusions and Future Work -- References -- 21 TR-SUM: An Automatic Text Summarization Tool for Turkish -- 21.1 Introduction -- 21.2 Literature Review -- 21.2.1 Related Studies in Turkish -- 21.2.2 Datasets in Turkish."]
[{"$nulls":4},"21.3 TR-SUM: A Text Summarization Tool for Turkish -- 21.3.1 General Overview of \"TR-SUM: A Text Summarization Tool for Turkish\" -- 21.3.2 TR-NEWS-SUM Dataset -- 21.3.3 Data Pre-processing -- 21.3.4 The Proposed Neural Network Models for Turkish Text Summarization -- 21.4 Discussion and Results -- 21.5 Conclusion and Future Work -- References -- 22 Automatic and Semi-automatic Bladder Volume Detection in Ultrasound Images -- 22.1 Introduction -- 22.2 Related Works -- 22.3 Method and Material -- 22.3.1 Data Set -- 22.3.2 Method -- 22.4 Discussion and Results -- 22.5 Conclusions and Future Work -- References -- 23 Effects of Variable UAV Speed on Optimization of Travelling Salesman Problem with Drone (TSP-D) -- 23.1 Introduction -- 23.2 Problem Definition -- 23.3 Methodology -- 23.3.1 Truck-Drone Algorithm Approach -- 23.4 Experimental Studies -- 23.4.1 Settings -- 23.4.2 Experimental Studies and Results -- 23.5 Discussions and Conclusion -- References -- 24 Improved Phasor Particle Swarm Optimization with Fitness Distance Balance for Optimal Power Flow Problem of Hybrid AC/DC Power Grids -- 24.1 Introduction -- 24.2 Mathematical Formulation of Optimal Power Flow Problem "]
[{"$nulls":4},"of Hybrid AC/DC Power Grids -- 24.2.1 State and Control Variables -- 24.2.2 Constraints -- 24.2.3 Objective Functions -- 24.3 Method -- 24.3.1 Fitness-Distance Balance Method -- 24.3.2 Overview of Phasor Particle Swarm Optimization (PPSO) Algorithm -- 24.3.3 Proposed FDBPPSO Algorithm -- 24.4 Experimental Settings -- 24.5 Results and Analysis -- 24.5.1 Determining the Best FDBPPSO Variant on CEC 2020 Test Suite -- 24.5.2 Application of the Proposed FDBPPSO Method for Optimal Power Flow Problem of Hybrid AC/DC Power Grids -- 24.6 Conclusions -- References."]
[{"$nulls":4},"25 Development of an FDB-Based Chimp Optimization Algorithm for Global Optimization and Determination of the Power System Stabilizer Parameters."]
[null,null,null,"Sommario/riassunto","This book brings together the most recent, quality research papers accepted and presented in the 3rd International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2021) held in Antalya, Turkey between 1-3 October 2021. Objective of the content is to provide important and innovative research for developments-improvements within different engineering fields, which are highly interested in using artificial intelligence and applied mathematics. As a collection of the outputs from the ICAIAME 2021, the book is specifically considering research outcomes including advanced use of machine learning and careful problem designs on human-centred aspects. In this context, it aims to provide recent applications for real-world improvements making life easier and more sustainable for especially humans. The book targets the researchers, degree students, and practitioners from both academia and the industry."]